"Combining RapidMiner with Python and R"
Hello everyone,
I am exploring RapidMiner, and I saw I can use Python and R in it.
I would love to get feedback from others that combine these three tools,
what is your typical workflow?
This is how I think about it.
R = academic / statistics
Python = practical ML / software engineering
RapidMiner = visual workflow / integration platform
One simple rule would be, if you can do it in RM then do it,
and if something has to be programmed then add Python / R operators in RM.
Thank you
I am exploring RapidMiner, and I saw I can use Python and R in it.
I would love to get feedback from others that combine these three tools,
what is your typical workflow?
This is how I think about it.
R = academic / statistics
Python = practical ML / software engineering
RapidMiner = visual workflow / integration platform
One simple rule would be, if you can do it in RM then do it,
and if something has to be programmed then add Python / R operators in RM.
Thank you
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New Altair Community Member
Accepted Answer
Hi @mlg1988
in my opinion R and Python help cover some niche cases which RapidMiner not yet covers, or does it poorly (e.g.: the web mining extension). If you work with the RapidMiner platform, you don't really need to program much, only a few lines to get some special functionality, via the scripting operators. The project framework that RM gives you is unparalleled in the R and Python world.
There are some cases when some tasks are easier to do with a script than in RapidMiner, in those cases I would insist with RM for a given time, because once you solve a problem in RM, the future use of the process (changes, debugging, operationalization) is better if you don't depend on external tools.
Regards,
Sebastian
New Altair Community Member
Not much to add, also for me Python allows me to cover the bits and pieces not available out of the box, or where python alternatives tend to be a bit faster on occasion. I've recently had a lot of fun dissecting pdf manuals and while the out of the box option in RM was a little 'mehh', being able to offload part of my workflow to python and back made it quite easy to do in the end.
Other stuff we use it for is dedicated API access, web crawling if the standard options don't do the job again, and disk / network input/output things. Also some python libraries (like Vader for sentiment analysis to just name one) make a nice extension to the tool set.
Other stuff we use it for is dedicated API access, web crawling if the standard options don't do the job again, and disk / network input/output things. Also some python libraries (like Vader for sentiment analysis to just name one) make a nice extension to the tool set.
Sort by:
1 - 1 of
11
New Altair Community Member
Accepted Answer
Hi @mlg1988
in my opinion R and Python help cover some niche cases which RapidMiner not yet covers, or does it poorly (e.g.: the web mining extension). If you work with the RapidMiner platform, you don't really need to program much, only a few lines to get some special functionality, via the scripting operators. The project framework that RM gives you is unparalleled in the R and Python world.
There are some cases when some tasks are easier to do with a script than in RapidMiner, in those cases I would insist with RM for a given time, because once you solve a problem in RM, the future use of the process (changes, debugging, operationalization) is better if you don't depend on external tools.
Regards,
Sebastian
I use to do some preprocessing on files that need some libraries in Python extension and apply deep learning in RM.